teenytest vs stestr comparison of testing frameworks
What are the differences between teenytest and stestr?

teenytest

https://github.com/testdouble/teenytest

stestr

https://pypi.org/project/stestr/
Programming language

JavaScript

Python

Category

Unit Testing

General info

Teenytest is a simple, zero-config test runner for NodeJS

Teenytest's CLI will run tests with zero public-API and zero configuration

stestr is a Python test runner designed to execute unittest test suites

stestr executes unittest test suites by using multiple processes to split up execution of a test suite then stores a history of all test runs to help in debugging failures and optimizing the scheduler to improve speed.
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

Yes

It supports xUnit output

No

Client-side
Allows testing code execution on the client, such as a web browser

No

Yes

Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour.
Server-side
Allows testing the bahovior of a server-side code

Yes

Teenytest tests database connections and other server-side components and behaviour

Yes

Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and behaviour.
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

It provides fixtures with the methods beforeAll(),afterEach() and afterAll()beforeAll() creates the browser and gives you a newPage() globalafterEach() will close any pages you created with newPage()afterAll() closes the browser

Yes

By use of a third party library like Fixture
Group fixtures
Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests.

Yes

Teeny test supports grouping of fixtures

By use of a third party library like Fixture
Generators
Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way.

Yes

By using a library like test-generator
Licence
Licence type governing the use and redistribution of the software

MIT License

Apache License 2.0

Mocks
Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed)

N/A

N/A

Grouping
Allows organizing tests in groups

Yes

Grouping is supported through nested tests in which any object can contain any combination of hooks, test functions, and additional sub-test objects.

N/A

Other
Other useful information about the testing framework